Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30291
Title: An investigation of reactive power planning based on chance constrained programming
Authors: Yang, N
Yu, C
Wen, F
Chung, CY
Keywords: Chance constrained programming
Genetic algorithm
Monte Carlo simulation
Reactive power planning
Uncertainties
Issue Date: 2007
Publisher: Elsevier
Source: International journal of electrical power and energy systems, 2007, v. 29, no. 9, p. 650-656 How to cite?
Journal: International journal of electrical power and energy systems 
Abstract: Deregulation in the electricity supply industry has brought many new challenges to the problem of reactive power planning. Although the problem has been extensively studied, available standard optimization models and methods do not offer good solutions to this problem, especially in a competitive electricity market environment where many factors are uncertain. Given this background, a novel method for reactive power planning based on chance constrained programming is presented in this paper, with uncertain factors taken into account. A stochastic optimization model is first formulated under the presumption that the generator outputs and load demands can be modeled as specified probability distributions. A method is then presented for solving the optimization problem using the Monte Carlo simulation method and genetic algorithm. Finally, a case study is used to illustrate the validity and essential features of the proposed model and methodology.
URI: http://hdl.handle.net/10397/30291
ISSN: 0142-0615
DOI: 10.1016/j.ijepes.2006.09.008
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